Understanding the Problem: Retrieving Previous Column Data

The given Stack Overflow question revolves around a common problem in data analysis - retrieving previous column values based on certain conditions. The questioner has a table named Score_calc with three columns: calc_pnt, score_id, and Regn_code. They want to query the database to fetch the maximum value of score_id that corresponds to a specific condition in the calc_pnt column.

Breaking Down the Conditions

The questioner has provided an example scenario where they need to find the previous score_id based on the calc_pnt value. For instance, if they are searching for values where calc_pnt <= 0.6, they want to retrieve the corresponding score_id value that is one step backward.

Let’s analyze the given SQL query:

select max(score_id)
from (select calc_pnt,score_id,lag(score_id) over(score_id) as previous
      from Score_calc
      where calc_pnt <= 0.6
     )

This query uses a subquery with an Common Table Expression (CTE) to calculate the previous score_id value for each row in the table.

How Lag() Function Works

The lag() function is used to access a previous row’s value within the result set. In this case, we are using it to get the previous score_id value for each row where calc_pnt <= 0.6.

Here’s how it works:

1. The select calc_pnt,score_id, lag(score_id) over(score_id) as previous part of the query fetches the current score_id and its corresponding previous score_id value.
2. The over(score_id) clause specifies that we want to calculate the previous score_id value based on the current row’s index in the table.
3. The max() function then returns the maximum value of score_id from the result set.

Limitations of the Query

The query provided by the answerer seems to be correct, but it has a limitation:

select max(score_id)
from Score_calc
where calc_pnt < 0.6 and regn_cd = 10;

This query only returns rows where regn_cd is equal to 10 and calc_pnt is less than 0.6. However, the questioner wants to retrieve the previous score_id value for each row where calc_pnt <= 0.6, regardless of the value in the regn_cd column.

Corrected Query

To achieve this, we need to modify the query to use a subquery with an aggregate function, such as max() or row_number(). Here’s an updated query that should meet the requirements:

with ranked_scores as (
  select calc_pnt,
         score_id,
         lag(score_id) over(order by calc_pnt) as previous_score_id
  from Score_calc
)
select max(previous_score_id)
from ranked_scores
where calc_pnt <= 0.6;

This query first ranks the rows in the table based on the calc_pnt value, and then uses the lag() function to get the previous score_id value for each row.

Using Row Number() Function

Alternatively, we can use the row_number() function to achieve a similar result:

with ranked_scores as (
  select calc_pnt,
         score_id,
         row_number() over(order by calc_pnt) as rn,
         lag(score_id) over(order by calc_pnt) as previous_score_id
  from Score_calc
)
select max(previous_score_id)
from ranked_scores
where rn = 2 and calc_pnt <= 0.6;

This query assigns a unique row number to each row in the table, based on the calc_pnt value. The lag() function is then used to get the previous score_id value for each row.

Conclusion

Retrieving previous column data based on certain conditions is a common problem in data analysis. By using subqueries with aggregate functions or CTEs with window functions, we can achieve this goal efficiently. In this article, we have discussed two approaches to solving this problem: using the lag() function and using the row_number() function. We hope that this explanation has helped you understand how to solve similar problems in your own work.

Last modified on 2024-05-08